Genetic Testing and Molecular Biomarkers

Because the IL-17/IL-17 receptor (IL-17R) axis is involved in lung inflammation and genetic variants, such as single nucleotide polymorphisms (SNPs), can affect its function, this study examined the associations between IL-17/IL-17R gene SNPs, serum IL-17A levels, and community-acquired pneumonia (CAP) in Iranian children.

A total of 266 subjects were enrolled in this study, comprising 126 children with CAP and 140 healthy controls. Genetic variants in the IL-17 and IL-17R genes were characterized by allele-specific PCR and PCR restriction fragment length polymorphism, respectively. Concurrently, serum IL-17A concentrations were measured by enzyme-linked immunosorbent assay.

Serum IL-17A levels were significantly higher in patients than in controls (295.8 ± 138.5 pg/mL vs. 40.6 ± 35.3 pg/mL, respectively; p = 0.001). Although the allele and genotype frequencies of IL-17 rs4711998 and IL-17 rs3748067 showed no significant association with CAP, the AA genotype and A allele of IL-17R rs4819554 were significantly more frequent in the patient group. Correlation analysis found no significant association between IL-17 genotypes and serum IL-17A levels. However, a significant positive correlation was observed between IL-17A levels and fever (p = 0.001).

The upregulation of IL-17A in patient sera and its correlation with fever support a role for IL-17A in the pathogenesis of CAP. Furthermore, the A allele and AA genotype of IL-17R rs4819554 were identified as potential risk factors for CAP in Iranian children. The lack of a significant association between IL-17 gene variants and serum IL-17A levels may be attributable to the complex regulatory network governing IL-17 production.

Glutathione-S-transferases (GSTs) play an important role in the detoxification and neutralization of oxidative stress products and xenobiotic compounds. Due to genetic polymorphisms in GST genes, GSTs partially or completely lose enzymatic activity, which may increase susceptibility to cardiovascular diseases. The objective of this study was to investigate hitherto unknown GSTM1 and GSTT1 null genotype frequencies in patients with coronary artery disease (CAD) and their potential association with CAD in the Bangladeshi population.

This study included 85 patients with CAD and 56 healthy control subjects confirmed by angiogram. Clinical parameters including triglyceride (TG), cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein levels were also evaluated. Genotypes of the GSTM1 and GSTT1 genes were identified using polymerase chain reaction followed by 1.5% (W/V) agarose gel electrophoresis with subsequent detection on a UV transilluminator.

There were significant differences in the null genotype distribution of GSTM1 and GSTT1 alleles between controls and patients with CAD. A significant association of the null genotype with CAD susceptibility (p < 0.05) was also observed. The combination of GSTM1 and GSTT1 null genes potentially increases the risk of CAD (odds ratio = 6.208; 95% confidence interval; p < 0.05). TG, LDL, and serum cholesterol levels were higher in patients with CAD (p < 0.05). GSTM1 and GSTT1 null genetic variations may be associated with increased susceptibility to CAD in the Bangladeshi population.

These findings suggest a potential association between GST gene polymorphisms and CAD susceptibility; however, larger studies are required to provide more robust and generalizable evidence in the Bangladeshi population.

The COVID-19 was the most amazing pandemic of the early third millennium, with significant variability in infection rates across regions worldwide. Genetic factors, particularly the ACE2 gene, coding for a common receptor implicated in facilitating SARS-CoV-2 entry into human cells, could play a crucial role in susceptibility to infection. Our study aimed to analyze the allelic frequency of four SNPs in ACE2 gene (rs4646127, rs2074192, rs2285666, rs112171234) and evaluate their correlations with COVID-19 infection rates in four regional samples from Morocco.

The total sample (N = 200) was obtained from: Rif (n = 50), Doukkala (n = 50), Ouarzazate (n = 49), and, Guelmim (n = 51). Genomic DNA was extracted using the GeneJET™ kit and genotyped by real-time PCR using TaqMan technology.

Analyses revealed significant spatial variations in the frequencies of alternative alleles of the studied SNPs, ranging from 0% to 74%. A significant positive correlation was observed between the frequency of alternative G allele of the rs4646127 and the infection rate variation (r = 0.96; p = 0.03; n = 4). Furthermore, significant differences reached 54.17% with worldwide populations (from North Africa, sub-Saharan Africa, Europe, Latino-America, East Asia, and South Asia) for the total SNP’s comparisons.

Our results suggest a significant positive correlation between the frequency of the alternative allele of the ACE2 gene polymorphism rs4646127 and COVID-19 regional infection rates in Morocco. This property could be exploited to consider this SNP as a potential biomarker for identifying at-risk groups. However, due to the limited number of regional samples, our results for all the analyzed SNPs remain exploratory and would require confirmation through larger-scale studies.

Biotinidase is an enzyme recycling endogenous biotin by hydrolyzing ε-N-biotinyl lysine (biocytin) to lysine and biotin. Biotin acts as a coenzyme in various carboxylation reactions. Biotinidase deficiency is rare, with an incidence of 1 per 112,271 individuals.

Genetic characterization of a 4-month-old boy born out of a consanguineous marriage presented with cutaneous manifestations, alopecia, developmental delay, hypotonia with absent neck holding, respiratory problems, and biotinidase deficiency.

Biochemical characterization was performed using tandem mass spectrometry and immunofluorescence enzyme assays. Pathogenic genetic variant was identified by Sanger sequencing of the BTD (biotinidase) gene in a patient and his parents.

Biochemical characterization indicated elevated methylmalonylcarnitine/hydroxyisovalerylcarnitine and decreased biotinidase, citrulline, glycine, and ornithine levels, suggesting a profound biotinidase deficiency. Sequencing of BTD gene indicates the presence of a 7-bp deletion and a 3-bp insertion (98-104del7ins3) in a homozygous state, resulting in a change of amino acid from cystine to phenylalanine at the 33rd position, causing a frameshift and premature amino acid termination at the 68th position.

A 7-bp deletion and a 3-bp insertion (98-104del7ins3) homozygous variation in the BTD gene segregating in a homozygous recessive manner in the family, causing truncated, nonfunctional biotinidase deficiency in the proband. This is a recurrent mutation and has the potential to be used as a biomarker for screening patients with biotinidase deficiency.

Phenylketonuria (PKU) is a genetic metabolic disorder caused by mutations in the phenylalanine hydroxylase (PAH) gene, with an incidence rate in China of approximately 1 in 11,000. PKU exhibits high heterogeneity, making the study of genotype–phenotype correlations essential for effective diagnosis and treatment.

This study aimed to analyze the genotype–phenotype correlation in pediatric PKU patients in China, with a special focus on hotspot mutations across different regions.

We compared the accuracy of two prediction models: the allele phenotype value/genotype–phenotype value system and the prediction system based on the sum of assigning value (AV) scores from PAH activity, evaluating both models based on available patient data from various regions.

The majority of genotypes in PKU patients were found to be compound heterozygotes. Classical PKU patients (cPKU) accounted for the highest proportion (44%), while the percentage of patients with mild hyperphenylalaninemia was relatively low at 22%. Among the eight regions studied, the APV/GPV system demonstrated higher accuracy (72.02%) compared with the AV score prediction system (56.82%, p < 0.05); however, for the cPKU phenotype alone, the difference in accuracy was not significant (p > 0.05).

This study provides insights into the relationship between genotypes and phenotypes in PKU patients across different regions of China, emphasizing the importance of analyzing hotspot mutations for understanding genotype–phenotype correlations. The findings highlight the need to enhance hotspot mutation spectra for PKU patients and advocate for the development of more accurate prediction models, which can offer better protection for PKU patients and alleviate the burden on patients and their families.